All of this is why, when I zoom out, @zama sits at the center of my “long-horizon” map for crypto.
Faster execution, cheaper fees, more modularity – those are all great, but they don’t answer the question of how billions of people will safely entrust real data and value to onchain systems. Fully homomorphic encryption does.
FHEVM turns that answer into something you can actually deploy, fork, and extend. I’m here accumulating knowledge, relationships and exposure around this ecosystem because it feels like the privacy base layer the next decade will quietly standardize on.
For me, this is exactly why I’m anchoring my time and energy around Zama right now – learning the FHEVM mental model, turning it into content, and positioning myself as someone who actually understands privacy as a core onchain primitive before the rest of CT catches up.
#ZamaCreatorProgram
GENESIS ARTIFACTS MINT DETAILS
SUPPLY: 10,000
DATE: August 18
GTD 3:00 PM UTC (11:00 AM ET)
MAX 5 PER WALLET
1 FREE + 4 (0.0012eth)
WL 4:00 PM UTC (12:00 PM ET)
MAX 10 PER WALLET
1 FREE + 9 (0.0014eth)
MINT + CHECKER:
https://t.co/pcAe2NvIyb
Link currently redirects to the application form
Mint page will go live closer to mint time
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In social science research, we are increasingly aware of the chilling effects of pervasive surveillance: people change their behavior when they know every action is recorded and analyzable.
Transparent ledgers exacerbate this by making financial and governance behavior permanently visible. By enabling encrypted computation onchain, @zama ’s FHEVM offers a way to retain the benefits of verifiability and programmability while removing some of the most intrusive aspects of observability.
Participants can act, vote, and transact under mathematically enforceable privacy guarantees, which may produce more authentic behavior and better data for researchers than heavily surveilled environments.
From a research and teaching standpoint, this is why I consider Zama, fully homomorphic encryption, and the FHEVM to be core infrastructure for the next decade of privacy-preserving Web3 applications, not just a passing narrative in crypto markets.
#ZamaCreatorProgram
For the AI safety community, @zama is relevant because it allows us to formalize limits on what powerful models and agents can access.
If the only interfaces available to an on-chain agent expose encrypted state and tightly scoped FHEVM functions, even a compromised or misaligned model cannot exfiltrate raw personal data from the ledger. It can act, optimize, and coordinate, but within a cryptographically constrained view of the world.
This is not a complete solution to AI risk, but it is a clean control at the infrastructure layer, made possible by fully homomorphic encryption becoming practical enough for live execution environments.
From a research and teaching standpoint, this is why I consider Zama, fully homomorphic encryption, and the FHEVM to be core infrastructure for the next decade of privacy-preserving Web3 applications, not just a passing narrative in crypto markets.
#ZamaCreatorProgram
..@zama is also interesting for those studying platform economics. Historically, platforms that treat user data as a resource to be harvested and sold have enjoyed strong network effects, but at the cost of trust and regulatory friction.
FHEVM suggests an alternative: platforms that cannot see raw data by design, and instead monetize computations, coordination, and guarantees. Because fully homomorphic encryption enforces this limitation at the protocol level, it is much harder for individual actors to quietly subvert it.
Over time, we may see “encrypted-by-default” platforms build a different kind of loyalty and attract users and institutions unwilling to accept the trade-offs of previous models.
From a research and teaching standpoint, this is exactly why I consider Zama, fully homomorphic encryption, and the FHEVM to be core infrastructure for the next decade of privacy-preserving Web3 applications, not just a passing narrative in crypto markets.
#ZamaCreatorProgram